Point Mutations at L1280 in Nav1.4 Channel D3-S6 Modulate Binding Affinity and Stereoselectivity of Bupivacaine Enantiomers

2003 ◽  
Vol 63 (6) ◽  
pp. 1398-1406 ◽  
Author(s):  
Carla Nau ◽  
Sho-Ya Wang ◽  
Ging Kuo Wang
Keyword(s):  
Binding Affinity ◽  
Point Mutations

scholarly journals In Silico Insights into HIV-1 Vpu-Tetherin Interactions and Its Mutational Counterparts

2019 ◽  
Vol 7 (6) ◽  
pp. 74
Author(s):  
Patil Sneha ◽  
Urmi Shah ◽  
Seetharaman Balaji
Keyword(s):  
Cell Surface ◽  
Binding Affinity ◽  
Hydrophobic Interactions ◽  
Single Point ◽  
Resistance Mechanism ◽  
Point Mutations ◽  
Protein Docking ◽  
Host Protein ◽  
Single Point Mutations ◽  
Hiv 1

Tetherin, an interferon-induced host protein encoded by the bone marrow stromal antigen 2 (BST2/CD317/HM1.24) gene, is involved in obstructing the release of many retroviruses and other enveloped viruses by cross-linking the budding virus particles to the cell surface. This activity is antagonized in the case of human immunodeficiency virus (HIV)-1 wherein its accessory protein Viral Protein U (Vpu) interacts with tetherin, causing its downregulation from the cell surface. Vpu and tetherin connect through their transmembrane (TM) domains, culminating into events leading to tetherin degradation by recruitment of β-TrCP2. However, mutations in the TM domains of both proteins are reported to act as a resistance mechanism to Vpu countermeasure impacting tetherin’s sensitivity towards Vpu but retaining its antiviral activity. Our study illustrates the binding aspects of blood-derived, brain-derived, and consensus HIV-1 Vpu with tetherin through protein–protein docking. The analysis of the bound complexes confirms the blood-derived Vpu–tetherin complex to have the best binding affinity as compared to other two. The mutations in tetherin and Vpu are devised computationally and are subjected to protein–protein interactions. The complexes are tested for their binding affinities, residue connections, hydrophobic forces, and, finally, the effect of mutation on their interactions. The single point mutations in tetherin at positions L23Y, L24T, and P40T, and triple mutations at {L22S, F44Y, L37I} and {L23T, L37T, T45I}, while single point mutations in Vpu at positions A19H and W23Y and triplet of mutations at {V10K, A11L, A19T}, {V14T, I18T, I26S}, and {A11T, V14L, A15T} have revealed no polar contacts with minimal hydrophobic interactions between Vpu and tetherin, resulting in reduced binding affinity. Additionally, we have explored the aggregation potential of tetherin and its association with the brain-derived Vpu protein. This work is a possible step toward an understanding of Vpu–tetherin interactions.

scholarly journals Alpha-actinin binding kinetics modulate cellular dynamics and force generation

2015 ◽  
Vol 112 (21) ◽  
pp. 6619-6624 ◽  
Author(s):  
Allen J. Ehrlicher ◽  
Ramaswamy Krishnan ◽  
Ming Guo ◽  
Cécile M. Bidan ◽  
David A. Weitz ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Cell Structure ◽  
Point Mutations ◽  
Traction Force ◽  
Human Kidney ◽  
Cell Dynamics ◽  
Motile Cells ◽  
Cross Linker ◽  
The Impact ◽  
In Cells

The actin cytoskeleton is a key element of cell structure and movement whose properties are determined by a host of accessory proteins. Actin cross-linking proteins create a connected network from individual actin filaments, and though the mechanical effects of cross-linker binding affinity on actin networks have been investigated in reconstituted systems, their impact on cellular forces is unknown. Here we show that the binding affinity of the actin cross-linker α-actinin 4 (ACTN4) in cells modulates cytoplasmic mobility, cellular movement, and traction forces. Using fluorescence recovery after photobleaching, we show that an ACTN4 mutation that causes human kidney disease roughly triples the wild-type binding affinity of ACTN4 to F-actin in cells, increasing the dissociation time from 29 ± 13 to 86 ± 29 s. This increased affinity creates a less dynamic cytoplasm, as demonstrated by reduced intracellular microsphere movement, and an approximate halving of cell speed. Surprisingly, these less motile cells generate larger forces. Using traction force microscopy, we show that increased binding affinity of ACTN4 increases the average contractile stress (from 1.8 ± 0.7 to 4.7 ± 0.5 kPa), and the average strain energy (0.4 ± 0.2 to 2.1 ± 0.4 pJ). We speculate that these changes may be explained by an increased solid-like nature of the cytoskeleton, where myosin activity is more partitioned into tension and less is dissipated through filament sliding. These findings demonstrate the impact of cross-linker point mutations on cell dynamics and forces, and suggest mechanisms by which such physical defects lead to human disease.

scholarly journals mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Thanh Binh Nguyen ◽  
Yoochan Myung ◽  
Alex G C de Sá ◽  
Douglas E V Pires ◽  
David B Ascher
Keyword(s):  
Nucleic Acid ◽  
Binding Affinity ◽  
Single Point ◽  
Point Mutations ◽  
Multiple Point ◽  
Missense Mutations ◽  
Nucleic Acid Binding ◽  
Single Point Mutations ◽  
Protein Nucleic Acid ◽  
Nucleic Acid Interactions

Abstract While protein–nucleic acid interactions are pivotal for many crucial biological processes, limited experimental data has made the development of computational approaches to characterise these interactions a challenge. Consequently, most approaches to understand the effects of missense mutations on protein-nucleic acid affinity have focused on single-point mutations and have presented a limited performance on independent data sets. To overcome this, we have curated the largest dataset of experimentally measured effects of mutations on nucleic acid binding affinity to date, encompassing 856 single-point mutations and 141 multiple-point mutations across 155 experimentally solved complexes. This was used in combination with an optimized version of our graph-based signatures to develop mmCSM-NA (http://biosig.unimelb.edu.au/mmcsm_na), the first scalable method capable of quantitatively and accurately predicting the effects of multiple-point mutations on nucleic acid binding affinities. mmCSM-NA obtained a Pearson's correlation of up to 0.67 (RMSE of 1.06 Kcal/mol) on single-point mutations under cross-validation, and up to 0.65 on independent non-redundant datasets of multiple-point mutations (RMSE of 1.12 kcal/mol), outperforming similar tools. mmCSM-NA is freely available as an easy-to-use web-server and API. We believe it will be an invaluable tool to shed light on the role of mutations affecting protein–nucleic acid interactions in diseases.

scholarly journals Structural modeling of the SARS-CoV-2 Spike/human ACE2 complex interface can identify high-affinity variants associated with increased transmissibility

2021 ◽  
Author(s):  
Hin Hark Gan ◽  
Alan Twaddle ◽  
Benoit Marchand ◽  
Kristin C. Gunsalus
Keyword(s):  
Binding Affinity ◽  
Three Dimensional ◽  
Point Mutations ◽  
Structural Modeling ◽  
Screening Methods ◽  
Susceptibility To Infection ◽  
High Affinity ◽  
Three Dimensional Modeling ◽  
Novel Variant ◽  
Natural Variants

AbstractThe COVID-19 pandemic has triggered concerns about the emergence of more infectious and pathogenic viral strains. As a public health measure, efficient screening methods are needed to determine the functional effects of new sequence variants. Here we show that structural modeling of SARS-CoV-2 Spike protein binding to the human ACE2 receptor, the first step in host-cell entry, predicts many novel variant combinations with enhanced binding affinities. By focusing on natural variants at the Spike-hACE2 interface and assessing over 700 mutant complexes, our analysis reveals that high-affinity Spike mutations (including N440K, S443A, G476S, E484R, G502P) tend to cluster near known human ACE2 recognition sites (K31 and K353). These Spike regions are conformationally flexible, allowing certain mutations to optimize interface interaction energies. Although most human ACE2 variants tend to weaken binding affinity, they can interact with Spike mutations to generate high-affinity double mutant complexes, suggesting variation in individual susceptibility to infection. Applying structural analysis to highly transmissible variants, we find that circulating point mutations S447N, E484K and N501Y form high-affinity complexes (~40% more than wild-type). By combining predicted affinities and available antibody escape data, we show that fast-spreading viral variants exploit combinatorial mutations possessing both enhanced affinity and antibody resistance, including S447N/E484K, E484K/N501Y and K417T/E484K/N501Y. Thus, three-dimensional modeling of the Spike/hACE2 complex predicts changes in structure and binding affinity that correlate with transmissibility and therefore can help inform future intervention strategies.

scholarly journals Design of a New α-1-C-Alkyl-DAB Derivative Acting as a Pharmacological Chaperone for β-Glucocerebrosidase Using Ligand Docking and Molecular Dynamics Simulation

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2683 ◽  
Author(s):  
Izumi Nakagome ◽  
Atsushi Kato ◽  
Noriyuki Yamaotsu ◽  
Tomoki Yoshida ◽  
Shin-ichiro Ozawa ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Binding Site ◽  
Binding Affinity ◽  
Gaucher Disease ◽  
Point Mutations ◽  
Dynamics Simulation ◽  
Ligand Docking ◽  
Pharmacological Chaperone ◽  
Pharmacological Chaperones ◽  
Dynamics Simulations

Some point mutations in β-glucocerebrosidase cause either improper folding or instability of this protein, resulting in Gaucher disease. Pharmacological chaperones bind to the mutant enzyme and stabilize this enzyme; thus, pharmacological chaperone therapy was proposed as a potential treatment for Gaucher disease. The binding affinities of α-1-C-alkyl 1,4-dideoxy-1,4-imino-d-arabinitol (DAB) derivatives, which act as pharmacological chaperones for β-glucocerebrosidase, abruptly increased upon elongation of their alkyl chain. In this study, the primary causes of such an increase in binding affinity were analyzed using protein–ligand docking and molecular dynamics simulations. We found that the activity cliff between α-1-C-heptyl-DAB and α-1-C-octyl-DAB was due to the shape and size of the hydrophobic binding site accommodating the alkyl chains, and that the interaction with this hydrophobic site controlled the binding affinity of the ligands well. Furthermore, based on the aromatic/hydrophobic properties of the binding site, a 7-(tetralin-2-yl)-heptyl-DAB compound was designed and synthesized. This compound had significantly enhanced activity. The design strategy in consideration of aromatic interactions in the hydrophobic pocket was useful for generating effective pharmacological chaperones for the treatment of Gaucher disease.

Point Mutations at N434 in D1-S6 of μ1 Na+ Channels Modulate Binding Affinity and Stereoselectivity of Local Anesthetic Enantiomers

1999 ◽  
Vol 56 (2) ◽  
pp. 404-413 ◽  
Author(s):  
Carla Nau ◽  
Sho-Ya Wang ◽  
Gary R. Strichartz ◽  
Ging Kuo Wang
Keyword(s):  
Binding Affinity ◽  
Local Anesthetic ◽  
Point Mutations ◽  
Na Channels

scholarly journals mmCSM-AB: guiding rational antibody engineering through multiple point mutations

2020 ◽  
Vol 48 (W1) ◽  
pp. W125-W131 ◽  
Author(s):  
Yoochan Myung ◽  
Douglas E V Pires ◽  
David B Ascher
Keyword(s):  
Binding Affinity ◽  
Single Point ◽  
Point Mutations ◽  
Affinity Maturation ◽  
Antibody Engineering ◽  
Multiple Point ◽  
Single Point Mutation ◽  
Atomic Interaction ◽  
Therapeutic Class ◽  
Antibody Design

Abstract While antibodies are becoming an increasingly important therapeutic class, especially in personalized medicine, their development and optimization has been largely through experimental exploration. While there have been many efforts to develop computational tools to guide rational antibody engineering, most approaches are of limited accuracy when applied to antibody design, and have largely been limited to analysing a single point mutation at a time. To overcome this gap, we have curated a dataset of 242 experimentally determined changes in binding affinity upon multiple point mutations in antibody-target complexes (89 increasing and 153 decreasing binding affinity). Here, we have shown that by using our graph-based signatures and atomic interaction information, we can accurately analyse the consequence of multi-point mutations on antigen binding affinity. Our approach outperformed other available tools across cross-validation and two independent blind tests, achieving Pearson's correlations of up to 0.95. We have implemented our new approach, mmCSM-AB, as a web-server that can help guide the process of affinity maturation in antibody design. mmCSM-AB is freely available at http://biosig.unimelb.edu.au/mmcsm_ab/.

scholarly journals How far are we in the rapid prediction of drug resistance caused by kinase mutations?

2020 ◽  
Author(s):  
Mehmet Erguven ◽  
Tülay Karakulak ◽  
M. Kasim Diril ◽  
Ezgi Karaca
Keyword(s):  
Protein Kinase ◽  
Protein Kinases ◽  
Binding Affinity ◽  
Point Mutations ◽  
Binding Pocket ◽  
Functional Study ◽  
Web Based ◽  
Diverse Range ◽  
Ligand Interactions ◽  
The Impact

ABSTRACTProtein kinases regulate various cell signaling events in a diverse range of species through phosphorylation. The phosphorylation occurs upon transferring the terminal phosphate of an ATP molecule to a designated target residue. Due to the central role of protein kinases in proliferative pathways, point mutations occurring within or in the vicinity of ATP binding pocket can render the enzyme overactive, leading to cancer. Combatting such mutation-induced effects with the available drugs has been a challenge, since these mutations usually happen to be drug resistant. Therefore, the functional study of naturally and/or artificially occurring kinase mutations have been at the center of attention in diverse biology-related disciplines. Unfortunately, rapid experimental exploration of the impact of such mutations remains to be a challenge due to technical and economical limitations. Therefore, the availability of kinase-ligand binding affinity prediction tools is of great importance. Within this context, we have tested six state-of-the-art web-based affinity predictors (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations with their ligand interactions. This assessment is performed on our structure-based protein kinase mutation benchmark, BINDKIN. BINDKIN contains 23 wild type-mutant pairs of kinase-small molecule complexes, together with their corresponding binding affinity data (in the form of IC50, Kd, and Ki). The web-server performances over BINDKIN show that the raw server predictions fail to produce good correlations with the experimental data. However, when we start looking in to the direction of change (whether a mutation improves/worsens the binding), we observe that over Ki data, DSX-ONLINE achieves a Pearson’s R correlation coefficient of 0.97. When we used homology models instead of crystal structures, this correlation drops to 0.45. These results highlight that there is still room to improve the available web-based predictors to estimate the impact of protein kinase point mutations. We present our BINDKIN benchmark and all the related results online for the sake of aiding such improvement efforts. Our files can be reached at https://github.com/CSB-KaracaLab/BINDKIN

scholarly journals Deep geometric representations for modeling effects of mutations on protein-protein binding affinity

2021 ◽  
Vol 17 (8) ◽  
pp. e1009284
Author(s):  
Xianggen Liu ◽  
Yunan Luo ◽  
Pengyong Li ◽  
Sen Song ◽  
Jian Peng
Keyword(s):  
Protein Binding ◽  
Binding Affinity ◽  
Protein Design ◽  
Protein Structures ◽  
Three Dimensional ◽  
Point Mutations ◽  
Dimensional Structure ◽  
Gradient Boosting ◽  
Benchmark Datasets ◽  
The Impact

Modeling the impact of amino acid mutations on protein-protein interaction plays a crucial role in protein engineering and drug design. In this study, we develop GeoPPI, a novel structure-based deep-learning framework to predict the change of binding affinity upon mutations. Based on the three-dimensional structure of a protein, GeoPPI first learns a geometric representation that encodes topology features of the protein structure via a self-supervised learning scheme. These representations are then used as features for training gradient-boosting trees to predict the changes of protein-protein binding affinity upon mutations. We find that GeoPPI is able to learn meaningful features that characterize interactions between atoms in protein structures. In addition, through extensive experiments, we show that GeoPPI achieves new state-of-the-art performance in predicting the binding affinity changes upon both single- and multi-point mutations on six benchmark datasets. Moreover, we show that GeoPPI can accurately estimate the difference of binding affinities between a few recently identified SARS-CoV-2 antibodies and the receptor-binding domain (RBD) of the S protein. These results demonstrate the potential of GeoPPI as a powerful and useful computational tool in protein design and engineering. Our code and datasets are available at: https://github.com/Liuxg16/GeoPPI.

Point mutations of human interleukin-1 with decreased receptor binding affinity

FEBS Letters ◽  
1986 ◽  
Vol 209 (2) ◽  
pp. 295-298 ◽  
Author(s):  
H.Robson MacDonald ◽  
Paul Wingfield ◽  
Ursula Schmeissner ◽  
Alan Shaw ◽  
G.Marius Clore ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Receptor Binding ◽  
Interleukin 1 ◽  
Point Mutations ◽  
Receptor Binding Affinity
Sign in / Sign up

Export Citation Format

Share Document